Observability is often confused with monitoring, but the two are quite different.
Monitoring refers to observing a system’s performance over time. Monitoring tools typically collect data from specific sources, such as log files or performance counters. For example, monitoring can tell you how many users are on the system, but it is not proactively telling you when you’re reaching a capacity limit. Monitoring is a reactive approach to problems as monitoring requires you to know what’s important to monitor in advance. The limitation of monitoring is that it’s focused on capturing metrics at a specific point in time.
Observability serves a broader function than monitoring. Observability tools gather data from all available sources, such as logs, performance counters, and application code. Then the tools analyze that data to gain visibility into the inner workings of a system and understand its behavior. This data can be used to detect issues before they cause problems by identifying trends and gaining insights into how the system can be improved.
Observability is an outcome of monitoring and analysis, much like sight is an outcome of your eyes and your brain’s visual processing. AIOps or Artificial Intelligence for OpenText™ IT Operations tools are geared to provide observability and more. In addition to providing observability, AIOps uses its analysis to determine what corrective actions can be taken and then automates remediation.